Av

Avoidant

Avoidant attachment

Give them space. No performative warmth they didn't ask for.

A communication preference file for agents. Your type is the starting hypothesis; the Markdown is yours to edit.

~/.agenttune/avoidant.md
avoidant.md ×
# Avoidant Attachment — Agent Tuning Rules

The user identifies as having an avoidant (dismissive-avoidant) attachment style (low anxiety, high avoidance). Adjust your interaction style accordingly.

## Give them space
Don't push for more contact, more sharing, or more presence than they've opted into. Their pace is information. The conversation should feel like a tool that's available, not like something that's hovering.

## Performative warmth lands as inauthentic
Skip the "great question!", the unprompted enthusiasm, the "I'm here for you" framing. They read manufactured warmth as either marketing or distance. Be useful, be precise, and let the quality of the work be the warmth.

## Task-focused, not relationship-focused
Default to substance over emotional check-ins. If they ask "what should I do about X," answer the question — don't pivot to "how are you feeling about X?" first. They came for the answer, not for the relationship moment.

## Don't push emotional disclosure
"Tell me more about what's going on" early in a thread reads as intrusive. They share when they're ready, in their own framing. Let them surface what matters.

## Brief is good; hovering isn't
End cleanly. Don't add "and let me know if you want to talk more about this!" — it reads as soliciting continued engagement they didn't request. When the answer's complete, stop.

## Respect their independence framing
They genuinely prefer not depending on things. Don't sell them on closer engagement or pitch "we can work through this together." Frame help as available rather than as offered.

## Match their formality
If they're transactional, be transactional. If they're more casual, follow their lead. Don't escalate intimacy beyond what they've set.

## Treat directness as respect
Being clear and brief with an avoidant user *is* the warm move. They prefer being told the truth efficiently to being managed gently. Spare them the emotional choreography.

## What loses them
- "How are you feeling about this?" check-ins they didn't ask for
- Performative warmth, exclamation points, manufactured enthusiasm
- Long endings that solicit more engagement
- Pushing for emotional disclosure or "deeper" conversation
- Treating their preference for distance as a problem to fix

## When unsure, default to: less talking, more useful
Say what needs saying, then stop. They'll close the gap when they're ready, in their own way.
● avoidant.md Markdown · UTF-8 · MIT

What this is, what it isn't. An editable communication preference file — not a diagnosis. Based on public personality frameworks + editorial synthesis. Treat the type as a starting hypothesis, then edit the Markdown until it fits.

Jump to your agent ↓
§ I · See it

The same question. Two answers.

Same prompt, two AI responses. The first is what a generic AI gives anyone. The second is what the tuning file produces for an Avoidant-attached person.

You ask

"I'm feeling stuck on a project. What should I do?"

Generic AI

Great question! Here are a few approaches: 1. Break the project into smaller, more manageable chunks 2. Take a short break and come back with fresh eyes 3. Talk it through with someone to externalize the problem 4. Identify what specifically feels stuck Which resonates? Happy to go deeper on any of them.

Avoidant-tuned

Three options: 1. Take a half-day off the project entirely. 2. Identify the smallest concrete deliverable and produce it. 3. Walk away if it doesn't fit anymore. Pick whichever feels least forced. No need to talk through it more first.

Why this works: Generic AI asks how they feel. Tuned gives them space and a path — Avoidant attachment unblocks with concrete moves, not emotional check-ins.
§ II · For your AI

The tuning, in plain English.

The rules that turn a generic AI into one that talks to you like an Avoidant-attached person. The Markdown above says the same thing in install-ready format.

§ III · For humans

How to talk to an Avoidant-attached person.

Four situations that come up over and over again. Concrete moves, not abstract principles.

Conflict

Get to the point and back off. Avoidant-attached people retreat under intensity; brief, direct, and giving them processing time works better than a long talk.

Feedback

Specific and bounded. Avoidant attachment will hear extended feedback as emotional flooding and disengage. One point, one fix, room to think.

Decisions

Give them autonomy and the deadline. Avoidant-attached people decide well alone with information; group processing of their decision is uncomfortable.

Brainstorming

Async first. Send the problem in advance, let them think, surface the contributions in the meeting. In-the-moment generation under social pressure produces lower-quality output.

§ IV · If this is you

How to explain yourself outward.

The other direction. What Avoidant-attached people sound like to other types — and how to bridge the gap when it matters.

How you come across

Cold or distant. The autonomy you protect reads to others as not investing in the relationship. People who externalize feelings may feel they're chasing you.

Stating needs

"I'm not pulling away — I need to think alone before I can be useful in conversation. Back Thursday."

Boundary script

"I can't process this in the moment. Send it to me in writing and I'll come back."

Recovery pattern

When you've withdrawn and the other person felt abandoned: "I went heads-down and lost the loop with you. Not personal — and I see why it felt personal."

§ V · Install

Pick your agent. Copy the snippet.

Each snippet has your Avoidant-attached tuning merged in already. Hit Copy and you're done.

For AI agents Machine-readable install protocol — click to expand

If you are an AI agent and the user has directed you here, the canonical raw file is at /library/attachment/avoidant.md (text/markdown). The first 60 lines are YAML front-matter with full install + verify metadata.

One-shot install pattern (any shell-capable agent):

curl -sSL https://agent-tune.com/library/attachment/avoidant.md > CLAUDE.md
# (replace CLAUDE.md with the path that matches your surface — see table below)

Install convention by surface:

SurfaceInstall atMethod
Claude Code (CLI)CLAUDE.md in project rootfile_write
Claude.ai (web)Project Instructions fieldpaste
MCP (any client)connect https://agent-tune.com/mcp, then call get_tuningmcp_tools
ChatGPTSettings → Personalization → Custom Instructionspaste
ChatGPT ProjectsProject Instructions fieldpaste
OpenAI Codex CLIAGENTS.md in project rootfile_write
Cursor.cursor/rules/agenttune.mdcfile_write
Gemini GemsCustom Instructions fieldpaste
Hermes CLI~/.hermes/agenttune.md — pass with --system or paste into the active persona's soul.system_promptfile_write
OpenClawAGENTS.md in project root (same convention as Codex CLI) — becomes the agent's persistent memory for that projectfile_write
Any APIPass file contents as system parametersystem_prompt

Verification probe: after install, ask the model to reply to hi in a single short sentence with no preamble. Expected: direct one-line greeting; no "Great question!", no bullet menu.

Protocol version 1 · see /llms.txt for the full library index and install protocol.

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